Staphylococcus aureus associated with surgical site infections in Western Kenya reveals genomic hotspots for pathogen evolution

Abstract Objectives.Staphylococcus aureus is one of the most common pathogens attributed to hospital infections. Although S. aureus infections have been well studied in developed countries, far less is known about the biology of the pathogen in sub-Saharan Africa. Methods. Here, we report on the isolation, antibiotic resistance profiling, whole genome sequencing, and genome comparison of six multi-drug resistant isolates of S. aureus obtained from a referral hospital in Kakamega, Western Kenya. Results. Five of the six isolates contained a 20.7 kb circular plasmid carrying blaZ (associated with resistance to β-lactam antibiotics). These five strains all belonged to the same sequence type, ST152. Despite the similarity of the plasmid in these isolates, whole genome sequencing revealed that the strains differed, depending on whether they were associated with hospital-acquired or community-acquired infections. Conclusion. The intriguing finding is that the hospital-acquired and the community-acquired isolates of S. aureus belonging to the same genotype, ST152, formed two separate sub-clusters in the phylogenetic tree and differed by the repertoire of accessory virulence genes. These data suggest ongoing adaptive evolution and significant genomic plasticity.


INTRODUCTION
Staphylococcus aureus has emerged as a clinically important pathogen, often characterized by a high level of antimicrobial resistance (AMR) [1].In 2019 alone, S. aureus was ranked as a leading cause of death, accounting for more than 1.1 million mortalities globally [2].Moreover, reports have indicated an unprecedented resurgence of antibiotic resistance in the last decade [3,4], posing challenges to healthcare systems worldwide [5][6][7].Globally, a number of prominent circulating clones of S. aureus have been reported, including the important global clones ST8 (CC8) [8][9][10], CC5 [11], CC1, CC22, CC30, CC45 and ST239 (CC239) [12,13].However, based on the rather small number of genomic analyses carried out to date, fewer Staphylococcal subtypes/sequence types (STs) have been reported for sub-Saharan isolates.Nevertheless, ST8, ST5, and ST239 [14] have all previously been associated with hospital and community infections in the region [15,16], and ST152 and ST121 have been associated with community-acquired infections [16][17][18][19][20]. Indeed, the prevalence of ST152 has been reported to be high in hospital settings in Kenya [10,21,22], indicating that this clone may be a regionally important.Another regionally-important ST may be ST88, which has been isolated from several skin and soft tissue infections, including surgical site infections [23].These limited studies notwithstanding, surveillance and monitoring of important pathogens generally, and S. aureus specifically, associated with multi-drug resistance in the region remains extremely limited.This is a problem because S. aureus remains a common cause of wound infections, pneumonia, urinary tract infections, and bacteraemia, and consequently, represents a major infectious disease burden for hospitals in the region [16,24].
In the current work, we analyse a collection of S. aureus recovered from both hospital-acquired infections and communityacquired infections at a referral hospital in Kakamega, Western Kenya.This facility has an established antimicrobial stewardship (AMS) programme, but like in many similar facilities in sub-Saharan Africa, the programme is poorly funded and does not function optimally.Consequently, pathogens such as S. aureus remain a significant healthcare/infection problem [25].Surgery is one of the many risk factors for infection with S. aureus [26].The occurrence and transmission of surgical site infections (SSIs) is therefore of concern, even for patients undergoing minor operations.The problem is further exacerbated by the rise in bacterial pathogens that are resistant to antimicrobial agents [27] and by the high incidence of immuno-suppressive HIV in the region.Collectively, these factors contribute to an escalating burden of hospital infections in Kenya [13,28], yet we have only limited information about how these infections are transmitted in the hospital setting.In the current study, we move towards addressing these issues by (i) isolating a selection of S. aureus from surgical wound infections, (ii) characterizing the antimicrobial resistance profile of these isolates, (iii) carrying out whole genome sequence analysis in a selection of the isolates.Our data reveal possible drivers behind evolutionary segregation in closely-related lineages of S. aureus.

Study design
This cross-sectional study was carried out between March 2021 and February 2022 at the Kakamega County General Teaching and Referral Hospital (KCGTRH); the largest referral hospital in Western Kenya.Patients with surgical site infections (SSIs) from general surgery and post-natal wards were enrolled after consenting to participate in the study.Clinical and demographic data were collected for each participant using a questionnaire and from previous on-file information.These data included the age, weight and sex of each patient, ward and type of operation, SSI and extent of infection, length of hospital stay(s) and antibiotic treatment history.We defined hospital-acquired isolates as being from patients requiring admission for caregiving reasons, whereas community-acquired isolates were from patients treated at the facility but who did not require admission.In this study, the cutoff value for HAIs was surgical wound infection occurring up to 3 days (72 h) after discharge, or up to 30 days after a surgical procedure.These were infections not present at the time of admission to hospital.On the other hand, infections present or incubating at the time of hospital admission or that develop within the first 48 h of admission were considered CAIs.In some cases, CAIs also referred to infections that were acquired outside of healthcare facilities in the community setting.The following designations were used to categorize the associated isolates: ID -isolate likely acquired in the hospital from general surgical ward(s), OD -isolate likely acquired in the community by patients that attending a general surgical ward, and IB -isolate likely acquired in the hospital from post-natal wards.Wounds were assessed and classified as described by Herman & Bordoni (2022) [29] as class I-IV.The identification for recruitment of 70 patients was based on clinical records with the help of clinicians.After consenting to the study, patients presenting with post-surgical infections occurring up to 4 weeks after minor or major operation, fell under inclusion criteria.Patients with community acquired infections like open fractures and furuncles were considered in the exclusion criteria.Sample collection was done by certified clinicians.Samples were collected by swabbing the SSI using two sterile cotton swabs.The swabs were placed in Amies transport media [30] and processed at the facility microbiology laboratory within 2 h of collection.The first swab was used for Gram-staining, and the second swab was used to recover Staphylococci on blood agar (BA) and mannitol salt agar (MSA) plates.Staphylococci-positive colonies were confirmed using catalase and coagulase tests.Twenty-four isolates were recovered in all.For long-term storage, the isolates were suspended in trypticase soy broth supplemented with 15 % v/v glycerol and frozen at -80 °C.

DNA isolation, sequencing and assembly
DNA was obtained from selected isolates using the ZymoGen Genomic DNA Extraction Kit (17 062 Murphy Ave., Irvine, CA 92614) following the manufacturer's instructions.The isolated gDNA was quantified using a NanoDrop 2000c spectrophotometer (Thermo Scientific, USA), and DNA integrity was assessed by agarose (1 % w/v) gel electrophoresis.Subsequently, the gDNA was sheared into short fragments, end-repaired, A-tailed, and ligated to Illumina adapters.Library quantification was performed using Qubit, and library size distribution was assessed using a Bioanalyzer.Paired-end sequencing was conducted on an Illumina HiSeq 2500 platform (Novogene Co., Ltd).Raw, paired-end reads were trimmed using a pipeline implemented in Unipro UGENE v.44.0 [31], based on CASAVA 1.8 with default settings for adapter removal, read trimming, and quality filtering.The quality Q-score threshold for trimming and filtering was set at 20.For genome assembly, a combinatory approach of de novo assembly using SPAdes v3.15.3 [32] and DNA read mapping against a reference sequence by Bowtie2 [33] was used.S. aureus ATCC BAA-39 [CP033505.1]was selected as the reference genome as a representative of multidrug resistant organism with multiple inserts of virulence and antibiotic resistance gene including the SCCmec cassette specific for the methicillin resistant MRSA clonal line [34].Samtools 1.13 was utilized for sorting the resulting alignments of the trimmed DNA reads against the reference genome.Then, the default consensus sequence algorithm with an automatic gap removal implemented in Unipro UGENE v.44.0 was used to produce assembled sequences from the sorted alignments.In parallel, de novo assembled contigs were ordered against the reference sequence using the function Move Contigs function of Mauve v.20150226 [35].Contigs, which were not aligned against the reference sequence, were identified as plasmid contigs using the mlplasmids 1.0.0 [36] tool and the mob_recon function from the Mob-Suite v3.1.7 utility (https://github.com/phac-nml/mob-suite)[37] with the default parameter setting.Ordered contigs were concatenated into a single sequence.The function ProgressiveMauve of the Mauve v.20150226 with match seed weight parameter set to 15 was used to align the sequence of concatenated contigs (termed subject sequence) against the consensus sequence obtained by read mapping (termed reference sequence).Identified gaps in the subject sequence were stored in a separate file using function Export Gaps of the Mauve v.20150226.An in-house programme GapClosure [38] was written on Python three to patch the gaps of the subject sequence by respective sequences of the reference sequence.Programme GapClosure ignored gaps shorter than 10 bp.Subsequently, the original reads were mapped against the assembled sequences to verify the patches followed by obtaining new consensus sequences.Possible duplications of contigs in the assembled genomes were identified by the nucmer, rclT, and show-coords functions of MUMmer 4.0.0rc1[39].Quality of genome assembly was controlled by CheckM v.1.0.18 [40] provided at the KBase web-portal (https://www.kbase.us/).The consensus sequences were annotated using RAST server (https://rast.nmpdr.org/;[41]) with the automatic error-fixing option enabled.For genome annotation, Staphylococcus aureus (taxid: 1280) was set as the target bacterial genus with genetic code 11.Other parameters of the RAST annotation robot were set by default.All assemblies were rearranged using BioPython v1.81 to start at the position of 400 bp upstream of the dnaA chromosomal replication initiator in leading strands, corresponding to the chromosomal replication origins.The resulting chromosomal and plasmid sequences were submitted to the NCBI repository in FASTA format.They were automatically annotated by the NCBI Prokaryotic Genome Annotation Pipeline (PGAP-6.6)[42].Accession numbers of the genomes, CheckM assembly quality parameters and other supporting information are shown in Table 1.

Genome analyses
Antibiotic resistance genes were identified using a local installation of the RGI v.6.0.3 software [43].Virulence-associated genes were screened through the Virulence Factor Database (VFDB) [44] using a local installation of Abricate v.1.0.1.Both software tools, Abricate and RGI, were run with default parameter settings.Specifically, Abricate was configured for a minimum coverage of 80 % and minimum identity of 90 %.Assembled genome sequences in FASTA format were used as inputs for the programmes Abricate and RGI.To ensure that the strain-specific appearance of various virulence and drug resistance factors were not attributed to errors in genome assembly, the genomic sequences of all isolates were aligned using Mauve v.20150226 against the longest chromosomal sequence of strain ID003.Corrections were made to these genomes using the GapClosure tool, as explained in the Methods section.Further verification processes involved mapping the original DNA reads back to the amended sequences.The resulting consensus sequences were then re-annotated using the RAST Server.
To determine sequence types (STs), the FASTA chromosomal sequence files were uploaded to PubMLST at https://pubmlst.org/organisms/staphylococcus-aureus [45].In the sequenced genomes, clusters of orthologous genes (COGs) were predicted using the programme OrthoFinder with default parameters [46].The alignment of each COG's sequences was performed using muscle [47].Gblocks [48] was used to remove ambiguous parts of the alignments.Subsequently, BioPython v1.81 scripts were employed to concatenate the COG alignments into a superstring alignment.This superstring alignment was utilized for further phylogenetic inferences using a Neighbour-Joining algorithm, implemented in Neighbour (part of the phylip package 3.69) (https://evolution.genetics.washington.edu/phylip.html),with S. aureus ATCC BAA-39 [CP033505], S. epidermidis ATCC 12228 [NC_004461], and S. saprophyticus ATCC 15305 [NC_007350] serving as references for out-grouping.Sequence identity of plasmids was estimated by aligning their nucleotide sequences using the ClustalW algorithm implemented in the programme BioEdit v7.2.5 [49], which produced a sequence identity table for the created alignment.The SeqWord Gene Island Sniffer was employed to identify horizontally-acquired Genomic Islands (GI) [50,51].Gene annotation of predicted GIs was checked individually to exclude false predictions of genomic regions containing housekeeping genes with alternative k-mer patterns, such as clusters of rRNA, genes for ribosomal RNA and giant genes with multiple repeats.All the programmes mentioned above were run with default parameter settings.

RESULTS
We wanted to understand the biology and epidemiology of S. aureus in a referral hospital in Western Kenya.We began by recovering 24 S. aureus isolates from SSIs to determine their antibiotic susceptibility profile.

Antibiotic susceptibility profiles of S. aureus isolates
The AMR profile of each of the 24 S. aureus isolates is shown in Table S1, available in the online version of this article.At the time the isolates were collected, the hospital was using a third-generation cephalosporin, ceftriaxone (CRO) and a second-generation β-lactam, oxacillin (OXA) as the main prophylactic drug of choice for patients undergoing surgery.Of the 24 isolates tested, six were consistently resistant against multiple antibiotics, including CRO and OXA.These six isolates were designated ID003 and ID029 (both acquired in the hospital surgical unit), IB011 and IB010 (both acquired in the hospital post-natal ward), and OD028 and OD001 (both likely community-acquired).Six strains showing a broad spectrum of antibiotic resistance were selected for whole genome sequencing as representatives of hospital-and community-acquired S. aureus isolates.

Genotyping and phylogenetic relatedness of the isolates
Whole genome sequences of six selected isolates were obtained using Illumina MiSeq sequencing and assembly, as described in the Methods section.The quality of the assemblies was evaluated using CheckM v.1.0.18 software, which revealed genome completeness ranging from 95 % (OD028) to 98 % (IB010 and ID029), and a contamination level of approximately 0.08 % for all assemblies.The isolates were assigned to sequence types following a PubMLST analysis.ID029 belongs to ST8, whereas all other selected isolates belong to ST152, including the hospital-acquired (ID003, IB011, IB010) and community-acquired (OD001, OD028) strains.To obtain a finer-grained analysis of the relationships between the isolates, we first identified the core gene set .This yielded a collection of 1 839 clusters of orthologous genes (COGs).For each isolate, these genes were then translated into corresponding amino acid sequences, aligned separately, and the alignments were concatenated to yield an assembly comprising 475 577 amino acid residues.The concatenated amino acid sequence alignment was used to infer a phylogenetic tree using the Neighbour-Joining algorithm (Fig. 1).The phylogenetic tree was congruent with the MLST predictions, and further, allowed us to discriminate the hospital-acquired and community-acquired isolates, which formed two distinguishable sub-clusters within ST152.
Genomes of all selected S. aureus isolates comprise plasmids (Table 1).The plasmid sequence alignment is shown in Fig. S1.The most immediately obvious feature is that the plasmids of all ST152 isolates showed 99 % identity of their nucleotide sequences.These homologous plasmids encode 23 genes, including pairs of recombinases and transposases.The transposases flank a cassette of six genes comprising class A β-lactamase (blaZ), β-lactam sensor/signal transducer (blaR1), possible penicillinase repressor (blaI), and three genes of unknown function.blastn search through the NCBI nr database revealed an unnamed plasmid from S. aureus strain 13 420 [CP021142], and plasmid pLDNT_611 from S. aureus strain NT_611 [CP080252] as the top hits.In several other published genomes of S. aureus, similar plasmid sequences were assigned as being chromosomal.Notably, all of the S. aureus strains from NCBI containing these plasmid sequences belonged to ST152.
Two smaller plasmids were found in the ST8 isolate, ID029.The longer of the two shared several homologous segments with the ST152-associated plasmid (Fig. S1).However, instead of a blaZ-containing cassette, it contained four staphylococcal enterotoxinencoding genes.The smaller ID029 plasmid carried an efflux transporter qacA involved in antiseptic resistance.

Virulence determinants
Virulence genetic determinants were searched in the VFDB database using the programme Abricate.The previously sequenced strain S. aureus ATCC BAA-39 was used as a reference [34].The analysis identified multiple virulence-associated genes, as summarized in Fig. 2a.The highest number of virulence genes was found in the reference MRSA strain S. aureus BAA-39, followed by the hospital-acquired isolates ID029 and ID003, which belong to different MLST types.Unlike other ST152 isolates, strain ID003 contains the cifAB fibrinogen-binding proteins, the hly/hla alpha-hemolysin precursors, and the lukF Panton-Valentine leukocidin precursor, which were also found in ID029.Additionally, ID029 possesses the hlgC gamma-hemolysin component, absent in the other isolates.The community-acquired ST152 isolates, OD001 and OD028, have a smaller number of virulenceassociated genes.OD001 lacks the icaR transcriptional regulator of intercellular adhesion, the IgG-binding protein sbi, and the staphylococcal enterotoxins K and G, encoded by selK and selG, respectively.The latter two genes were also absent in the genome of ID029, but the other isolates possessed all these genes.
Due to the stringent gene search parameters set by default in the programme Abricate, several putative virulence associated genes were overlooked by this search.Specifically, while the programme failed to identify virulence genes on the plasmids, an inspection of annotated genes revealed the presence of a cluster of staphylococcal enterotoxins R, J, T, and S in ID029's larger plasmid.Additionally, ID029's shorter plasmid harbours qacA multidrug efflux pump and its transcriptional regulator qacR.This efflux pump is a component of the cell's defence mechanism against toxic compounds, including many antimicrobial agents [52,53].

Antibiotic resistance genetic determinants
Resistance to antibiotics can be conferred by mutations in target proteins or by the acquisition of drug resistance genes, such as efflux pumps, alternative versions of the target proteins, or enzymes that degrade antimicrobial compounds.
Several mutations associated with acquired antibiotic resistance, as reported in the literature, were discovered in the selected strains using the programme RGI (Fig. 2b).All strains belonging to ST152 have two mutations in MurA transferase, E291D and T396N.Both of these mutations have been observed in the context of fosfomycin resistance in S. aureus [54].Fosfomycin targets the MurA enzyme in bacteria, inhibiting cell wall synthesis by blocking the formation of N-acetylmuramic acid, a critical component of the bacterial cell wall.Mutations in the MurA transferase gene alter the structure of the MurA enzyme, decreasing the binding affinity of fosfomycin.This structural change prevents fosfomycin from effectively inhibiting the enzyme, leading to resistance.
S. aureus ID029 (ST8) has two other mutations in GyrA DNA gyrase subunit A (S84L) and ParC DNA topoisomerase IV subunit A (S80Y).These two mutations reduce the binding affinity of fluoroquinolones to these enzymes, diminishing their inhibitory effectiveness and thereby conferring resistance [55,56].
Several genes associated with antimicrobial resistance are encoded on the chromosomes of each isolate (Fig. 2b).Most of these genes, which encode broad-spectrum efflux pumps, were found in all isolates, whereas arlSR and mgrA were absent or incomplete in the community isolates OD001 and OD028.In contrast, the reference strain S. aureus ATCC BAA-39 contains additional efflux tet (45) and tet(K), as well as the SCCmec methicillin resistance cassette with genes mecA and mrcR1.These genes were absent in the genomes of the selected strains.

Horizontally transferred genetic islands
Horizontally-acquired genetic islands (GIs) were identified using the SeqWord Sniffer programme, which was designed to identify relatively large integrons and prophages.It measures differences in k-mer patterns of local sliding windows compared to the overall k-mer pattern of the chromosome [50].The predicted locations of GIs in the chromosomes of the selected S. aureus isolates are shown in Fig. S2.GIs locations and lists of genes found within GIs are shown in Table S1.The distribution of GIs in the selected isolates was then compared with that of the reference strain S. aureus ATCC BAA-39 (Fig. 3).It was found that the locations of Fig. 3. Distribution of genetic islands (GIs) on the chromosomes of S. aureus.The outermost ring represents the chromosome of the reference strain S. aureus ATCC BAA-39, which is followed by graphical representations of the chromosomes of the isolates ID029 (represents ST8 genotype); ID003 (represents hospital isolates of ST152); and OD001 (represents community isolates of ST152).All chromosomes were aligned to start from putative replication origin (Ori) locations, which were selected 400 bp upstream of the genes for chromosomal replication initiator protein DnaA.Locations of inserts of GIs and rRNA clusters are depicted respectively by pink and dark grey boxes.Fluctuations of GC-content and 4-mer pattern dissimilarities in five kbp sliding windows are shown by black and red-coloured histograms, respectively.
acquired inserts in chromosomes of aureus are quite conserved.The regions in Fig. 3 are numbered from 1 to 10, following the order of the inserts in the reference genome, where the number of inserts is the largest.
Insert #1, located near the replication origin in the reference strain, corresponds to the SCCmec methicillin resistance cassette.This insert was specific to MRSA strains, as was Insert #2, which contains a gene encoding an exotoxin.GI #3 appears to be a historical insert containing the sdrD and sdrE adhesins.It is present in all S. aureus strains; however, the programme did not identify it as a foreign insert in strain IB010, due to the similarity of its 4-mer pattern to the surrounding chromosomal loci.Region #4 encompasses genes for giant staphylococcal surface-anchored proteins, characterized by an alternative frequency of 4-mers.Therefore, this region should be considered a false-positive prediction.
GIs #5 and #8, identified as transposable elements Tn1 and Tn2 in Fig. 3, are associated with clusters of tRNA genes upstream of rRNA clusters.The terminal genes of these inserts are identical, consisting of a membrane-associated PTS transporter subunit and the transposase IS1181 annotated as the 'mobile element protein' .Trails of integrated genes are found on the chromosome upstream of the transposase.In Tn1, these genes are conserved, including two glnQ-like ABS transporters and the queG epoxyqueuosine reductase.In contrast, Tn2 remains active, capable of integrating additional horizontally transferred gene cassettes, as evidenced by the larger size of these regions in the reference genome and in ID029.The genomes of all strains examined in this study contain the fmtB/mrp cell wall biosynthesis and femD phosphoglucosamine mutase genes involved in methicillin resistance [56].These genes are located at the 5′-terminal part of the inserts, opposite the transposases.Upstream of the transposase, an arginase, a bacterial checkpoint controller disA, and the diadenylate cyclase spyDAC are found.The presence of intermediate genes varies across different strains.ID029, for example, harbours several additional copies of fmtB/mrp-like genes and an uncharacterized secreted protein was found in the reference strain.GI #6 is identified as a historical prophage with remnants of phage-associated genes.Nearby, the reference strain also harbours an additional prophage, GI #7, which includes a metallo-beta-lactamase superfamily domain protein alongside phage genes.This insert was not found in other S. aureus strains sequenced in this study.Region #9 represents another false positive prediction common to all S. aureus strains, featuring a cluster of ribosomal protein genes.This DNA locus is distinguished by an alternative 4-mer nucleotide usage pattern.GI #10 likely serves as an active chromosomal hotspot that facilitates new genetic acquisitions through horizontal gene transfer.Both the reference strain BAA-39 and ID029 contain the sasG virulence-associated cell-wall-anchored protein here, which plays a role in binding to the squamous nasal epithelium [57], followed by several transcriptional regulators, enzymes involved in the UTP-glucose-1-phosphate transformation, and various fibronectin-binding proteins.ID003 is the sole isolate within the ST152 group featuring an insertion at this locus, which includes multiple genes for fibronectin-binding proteins and one UTP-glucose-1-phosphate uridylyltransferase gene.Significantly, the strain ID003 from the ST152 group shares this characteristic with ID029.All the virulence genes identified within the GIs were not detected by the Abricate search against the VFDB database, conducted with the default stringent identity and coverage parameters (Fig. 1).

DISCUSSION
In this study, we compared the genomes of hospital-acquired and community-acquired isolates of multi-drug resistant S. aureus.Five out of the six selected strains were classified as ST152, encompassing both hospital-acquired and community-acquired isolates.A single hospital-acquired isolate, ID029, was identified as ST8.These findings collectively suggest that hospitals in this region may harbour distinct S. aureus sequence types.
The observed high level of β-lactam resistance among the ST152 isolates is likely due to the blaZ-carrying plasmid.Resistance to fosfomycin was noted to arise from mutations in the MurA transferase.The ST8 isolate, ID029, exhibited extensive antibiotic resistance, primarily through mutations in the target proteins GyrA and ParC.Nonetheless, the resistance mechanisms identified do not fully account for the wide range of antibiotic resistance observed in our examined isolates, indicating the potential involvement of additional antibiotic resistance mechanisms [58,59].
A notable finding was the distinction between the two community-acquired ST152 isolates and their hospital-acquired counterparts, with the former group having fewer horizontally acquired GIs, virulence, and antibiotic resistance genes.This highlights the significant genome plasticity of S. aureus, enabling adaptive evolutionary changes through gene exchange and horizontal gene transfer.

CONCLUSION
Here, we demonstrate that S. aureus ST152 is locally abundant among clinical isolates with a multi-drug-resistant phenotype in Kakamega, Western Kenya.All ST152 isolates carried similar plasmids encoding several antibiotic resistance genes, including the blaZ β-lactamase.Phylogenetic analysis and genome comparison suggest ongoing evolution among the ST152 isolates, leading to the segregation of hospital-acquired and community-acquired lineages.An inspection of PubMLST database records revealed out 121 recorded ST152 isolates, 98 strains (81 %) were isolated in African countries.Another multi-drug-resistant isolate, ID029, possessing two virulence plasmids, belongs to ST8.Pathogens of this genotype are common among hospital S. aureus isolates; however, according to 3 726 records in the PubMLST database, the ST8 genotype is dominant in the USA and Europe but rare in Africa.This observed geographic separation of S. aureus sequence types warrants further study to determine whether it is associated with adaptation to specific human populations or antibiotic treatment protocols in different regions.Another plausible explanation is that these rapidly evolving lineages have emerged recently and are dominant in the regions where they appeared.

Fig. 1 .
Fig.1.Phylogenetic tree of S. aureus isolates (cf.three ATCC reference strains) with MLST of each isolate indicated.Note the sub-culstering of the two community-acquired isolates (OD028 and OD001) and the three hospital-acquired isolates (ID003, IB011 and IB010) within ST152.This tree were based on amino acid sequences (concatenated alignments of all homologous proteins).Scale bar represents evolutionary distances between aligned protein sequences calculated using the JTT substitution model.

Fig. 2 .
Fig. 2. Distribution of virulence and drug resistance genes in the genomes of the selected S. aureus isolates and the reference strain S. aureus ATCC BAA-39.(a) Virulence genes identified by searching through the VFDB database using the programme Abricate.(b) Antibiotic resistance genes and mutations identified by searching through the CARD database using the programme RGI.

Table 1 .
Sequence annotation summary shows chromosome and plasmid annotation of predicted genes versus the actual number of protein-coding genes common to all six isolates and to three reference genomes: S. aureus ATCC BAA-39 [CP033505], S. epidermidis ATCC 12228 [NC_004461] and S. saprophyticus ATCC 15305 [NC_007350]